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<div class="title">prosac.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2009, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *  Copyright (c) 2012-, Open Perception, Inc.</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> * $Id$</span></div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160; </div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#ifndef PCL_SAMPLE_CONSENSUS_IMPL_PROSAC_H_</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;<span class="preprocessor">#define PCL_SAMPLE_CONSENSUS_IMPL_PROSAC_H_</span></div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160; </div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#if defined __GNUC__</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;<span class="preprocessor">#  pragma GCC system_header </span></div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;<span class="preprocessor">#include &lt;boost/math/distributions/binomial.hpp&gt;</span></div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;<span class="preprocessor">#include &lt;pcl/sample_consensus/prosac.h&gt;</span></div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160; </div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;<span class="comment">// Variable naming uses capital letters to make the comparison with the original paper easier</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">bool</span> </div>
<div class="line"><a name="l00054"></a><span class="lineno"><a class="line" href="classpcl_1_1_progressive_sample_consensus.html#a34454e62b3ddbd4c9e5da601a7ced3b8">   54</a></span>&#160;<a class="code" href="classpcl_1_1_progressive_sample_consensus.html#a34454e62b3ddbd4c9e5da601a7ced3b8">pcl::ProgressiveSampleConsensus&lt;PointT&gt;::computeModel</a> (<span class="keywordtype">int</span> debug_verbosity_level)</div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;{</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;  <span class="comment">// Warn and exit if no threshold was set</span></div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;  <span class="keywordflow">if</span> (threshold_ == DBL_MAX)</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;  {</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::ProgressiveSampleConsensus::computeModel] No threshold set!\n&quot;</span>);</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  }</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160; </div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;  <span class="comment">// Initialize some PROSAC constants</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> T_N = 200000;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">size_t</span> N = sac_model_-&gt;indices_-&gt;size ();</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">size_t</span> m = sac_model_-&gt;getSampleSize ();</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  <span class="keywordtype">float</span> T_n = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (T_N);</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; m; ++i)</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;    T_n *= <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (m - i) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (N - i);</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;  <span class="keywordtype">float</span> T_prime_n = 1.0f;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  <span class="keywordtype">size_t</span> I_N_best = 0;</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  <span class="keywordtype">float</span> n = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (m);</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160; </div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;  <span class="comment">// Define the n_Start coefficients from Section 2.2</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keywordtype">float</span> n_star = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (N);</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  <span class="keywordtype">float</span> epsilon_n_star = 0.0;</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="keywordtype">size_t</span> k_n_star = T_N;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160; </div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;  <span class="comment">// Compute the I_n_star_min of Equation 8</span></div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  std::vector&lt;unsigned int&gt; I_n_star_min (N);</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;  <span class="comment">// Initialize the usual RANSAC parameters</span></div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;  iterations_ = 0;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160; </div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;  std::vector&lt;int&gt; inliers;</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;  std::vector&lt;int&gt; selection;</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;  Eigen::VectorXf model_coefficients;</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160; </div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;  <span class="comment">// We will increase the pool so the indices_ vector can only contain m elements at first</span></div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;  std::vector&lt;int&gt; index_pool;</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  index_pool.reserve (N);</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> i = 0; i &lt; n; ++i)</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;    index_pool.push_back (sac_model_-&gt;indices_-&gt;operator[](i));</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160; </div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="comment">// Iterate</span></div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;  <span class="keywordflow">while</span> (<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span> (iterations_) &lt; k_n_star)</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;  {</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;    <span class="comment">// Choose the samples</span></div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160; </div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;    <span class="comment">// Step 1</span></div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;    <span class="comment">// According to Equation 5 in the text text, not the algorithm</span></div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;    <span class="keywordflow">if</span> ((iterations_ == T_prime_n) &amp;&amp; (n &lt; n_star))</div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;    {</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      <span class="comment">// Increase the pool</span></div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      ++n;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;      <span class="keywordflow">if</span> (n &gt;= N)</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;        <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;      index_pool.push_back (sac_model_-&gt;indices_-&gt;at(<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span> (n - 1)));</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;      <span class="comment">// Update other variables</span></div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;      <span class="keywordtype">float</span> T_n_minus_1 = T_n;</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      T_n *= (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(n) + 1.0f) / (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(n) + 1.0f - <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(m));</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      T_prime_n += ceilf (T_n - T_n_minus_1);</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;    }</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160; </div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;    <span class="comment">// Step 2</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;    sac_model_-&gt;indices_-&gt;swap (index_pool);</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;    selection.clear ();</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    sac_model_-&gt;getSamples (iterations_, selection);</div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    <span class="keywordflow">if</span> (T_prime_n &lt; iterations_)</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    {</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;      selection.pop_back ();</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;      selection.push_back (sac_model_-&gt;indices_-&gt;at(<span class="keyword">static_cast&lt;</span><span class="keywordtype">unsigned</span> <span class="keywordtype">int</span><span class="keyword">&gt;</span> (n - 1)));</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    }</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;    <span class="comment">// Make sure we use the right indices for testing</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;    sac_model_-&gt;indices_-&gt;swap (index_pool);</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160; </div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;    <span class="keywordflow">if</span> (selection.empty ())</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    {</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;      PCL_ERROR (<span class="stringliteral">&quot;[pcl::ProgressiveSampleConsensus::computeModel] No samples could be selected!\n&quot;</span>);</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;    }</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;    <span class="comment">// Search for inliers in the point cloud for the current model</span></div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;    <span class="keywordflow">if</span> (!sac_model_-&gt;computeModelCoefficients (selection, model_coefficients))</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;    {</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;      ++iterations_;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;      <span class="keywordflow">continue</span>;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    }</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160; </div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;    <span class="comment">// Select the inliers that are within threshold_ from the model</span></div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    inliers.clear ();</div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    sac_model_-&gt;selectWithinDistance (model_coefficients, threshold_, inliers);</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160; </div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;    <span class="keywordtype">size_t</span> I_N = inliers.size ();</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160; </div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;    <span class="comment">// If we find more inliers than before</span></div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">if</span> (I_N &gt; I_N_best)</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    {</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;      I_N_best = I_N;</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160; </div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;      <span class="comment">// Save the current model/inlier/coefficients selection as being the best so far</span></div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;      inliers_ = inliers;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;      model_ = selection;</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;      model_coefficients_ = model_coefficients;</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160; </div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;      <span class="comment">// We estimate I_n_star for different possible values of n_star by using the inliers</span></div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      std::sort (inliers.begin (), inliers.end ());</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160; </div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;      <span class="comment">// Try to find a better n_star</span></div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;      <span class="comment">// We minimize k_n_star and therefore maximize epsilon_n_star = I_n_star / n_star</span></div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;      <span class="keywordtype">size_t</span> possible_n_star_best = N, I_possible_n_star_best = I_N;</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;      <span class="keywordtype">float</span> epsilon_possible_n_star_best = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(I_possible_n_star_best) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(possible_n_star_best);</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160; </div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;      <span class="comment">// We only need to compute possible better epsilon_n_star for when _n is just about to be removed an inlier</span></div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;      <span class="keywordtype">size_t</span> I_possible_n_star = I_N;</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;      <span class="keywordflow">for</span> (std::vector&lt;int&gt;::const_reverse_iterator last_inlier = inliers.rbegin (), </div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;                                                    inliers_end = inliers.rend (); </div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;           last_inlier != inliers_end; </div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;           ++last_inlier, --I_possible_n_star)</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;      {</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;        <span class="comment">// The best possible_n_star for a given I_possible_n_star is the index of the last inlier</span></div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;        <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> possible_n_star = (*last_inlier) + 1;</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;        <span class="keywordflow">if</span> (possible_n_star &lt;= m)</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;          <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160; </div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;        <span class="comment">// If we find a better epsilon_n_star</span></div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;        <span class="keywordtype">float</span> epsilon_possible_n_star = <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(I_possible_n_star) / <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(possible_n_star);</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;        <span class="comment">// Make sure we have a better epsilon_possible_n_star</span></div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;        <span class="keywordflow">if</span> ((epsilon_possible_n_star &gt; epsilon_n_star) &amp;&amp; (epsilon_possible_n_star &gt; epsilon_possible_n_star_best))</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;        {</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;          <span class="comment">// Typo in Equation 7, not (n-m choose i-m) but (n choose i-m)</span></div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;          <span class="keywordtype">size_t</span> I_possible_n_star_min = m</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                           + <span class="keyword">static_cast&lt;</span><span class="keywordtype">size_t</span><span class="keyword">&gt;</span> (ceil (boost::math::quantile (boost::math::complement (boost::math::binomial_distribution&lt;float&gt;(<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (possible_n_star), 0.1f), 0.05))));</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;          <span class="comment">// If Equation 9 is not verified, exit</span></div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;          <span class="keywordflow">if</span> (I_possible_n_star &lt; I_possible_n_star_min)</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;            <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;          possible_n_star_best = possible_n_star;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;          I_possible_n_star_best = I_possible_n_star;</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;          epsilon_possible_n_star_best = epsilon_possible_n_star;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;        }</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      }</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160; </div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;      <span class="comment">// Check if we get a better epsilon</span></div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;      <span class="keywordflow">if</span> (epsilon_possible_n_star_best &gt; epsilon_n_star)</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      {</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;        <span class="comment">// update the best value</span></div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;        epsilon_n_star = epsilon_possible_n_star_best;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160; </div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;        <span class="comment">// Compute the new k_n_star</span></div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        <span class="keywordtype">float</span> bottom_log = 1 - std::pow (epsilon_n_star, <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span>(m));</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;        <span class="keywordflow">if</span> (bottom_log == 0)</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;          k_n_star = 1;</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        <span class="keywordflow">else</span> <span class="keywordflow">if</span> (bottom_log == 1)</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;          k_n_star = T_N;</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;        <span class="keywordflow">else</span></div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;          k_n_star = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (ceil (log (0.05) / log (bottom_log)));</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;        <span class="comment">// It seems weird to have very few iterations, so do have a few (totally empirical)</span></div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;        k_n_star = (std::max)(k_n_star, 2 * m);</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;      }</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;    }</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160; </div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;    ++iterations_;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <span class="keywordflow">if</span> (debug_verbosity_level &gt; 1)</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::ProgressiveSampleConsensus::computeModel] Trial %d out of %d: %d inliers (best is: %d so far).\n&quot;</span>, iterations_, k_n_star, I_N, I_N_best);</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;    <span class="keywordflow">if</span> (iterations_ &gt; max_iterations_)</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;    {</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;      <span class="keywordflow">if</span> (debug_verbosity_level &gt; 0)</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;        PCL_DEBUG (<span class="stringliteral">&quot;[pcl::ProgressiveSampleConsensus::computeModel] RANSAC reached the maximum number of trials.\n&quot;</span>);</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;    }</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  }</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160; </div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  <span class="keywordflow">if</span> (debug_verbosity_level &gt; 0)</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    PCL_DEBUG (<span class="stringliteral">&quot;[pcl::ProgressiveSampleConsensus::computeModel] Model: %lu size, %d inliers.\n&quot;</span>, model_.size (), I_N_best);</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  <span class="keywordflow">if</span> (model_.empty ())</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;  {</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;    inliers_.clear ();</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;    <span class="keywordflow">return</span> (<span class="keyword">false</span>);</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;  }</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160; </div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;  <span class="keywordflow">return</span> (<span class="keyword">true</span>);</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;}</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160; </div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;<span class="preprocessor">#define PCL_INSTANTIATE_ProgressiveSampleConsensus(T) template class PCL_EXPORTS pcl::ProgressiveSampleConsensus&lt;T&gt;;</span></div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160; </div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;<span class="preprocessor">#endif    </span><span class="comment">// PCL_SAMPLE_CONSENSUS_IMPL_PROSAC_H_</span></div>
<div class="ttc" id="aclasspcl_1_1_progressive_sample_consensus_html_a34454e62b3ddbd4c9e5da601a7ced3b8"><div class="ttname"><a href="classpcl_1_1_progressive_sample_consensus.html#a34454e62b3ddbd4c9e5da601a7ced3b8">pcl::ProgressiveSampleConsensus::computeModel</a></div><div class="ttdeci">bool computeModel(int debug_verbosity_level=0)</div><div class="ttdoc">Compute the actual model and find the inliers</div><div class="ttdef"><b>Definition:</b> prosac.hpp:54</div></div>
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